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Purpose: Assessing change remains a challenge in patient-reported outcomes. In June 2009, a group of psychometricians, biostatisticians, and behavioral researchers from other disciplines convened as a Longitudinal Analysis of Patient-Reported Outcomes Working group as part of the Statistical and Applied Mathematical Sciences Institute Summer Psychometric program to discuss the complex issues that arise when conceptualizing and operationalizing "change" in patient-reported outcome (PRO) measures and related constructs. This white paper summarizes these issues and provides recommendations and possible paths for dealing with the complexities of measuring change., Methods/results: This article presents and discusses issues associated with: (1) conceptualizing and operationalizing change in PRO measures; (2) modeling change using state-of-the-art statistical methods; (3) impediments to detecting true change; (4) new developments to deal with these challenges; and (5) important gaps that are fertile ground for future research., Conclusions: There was a consensus that important research still needs to be performed in order develop and refine high-quality PRO measures and statistical methods to analyze and model change in PRO constructs.

Objectives: We sought to develop a mapping function from functional assessment of cancer therapy-melanoma (FACT-M) quality of life scores to the EuroQol-5D (EQ-5D) utility scores., Methods: FACT-M and EQ-5D scores were collected during a prospective study of melanoma-related quality of life at a tertiary cancer care center in the United States. The study sample was divided into development and validation datasets with equal distributions by cancer stage and treatment status. Censored Least Absolute Deviation (CLAD) and Ordinary Least Squares (OLS) regression analyses were performed using the developmental dataset to derive mapping functions, and model performance was examined through comparisons of residuals and measures of fit in the validation dataset. Exploratory analyses examined the predictive ability of clinical factors and individual subscales., Results: Of 273 patients, 75 were undergoing treatment with 198 in follow-up surveillance. Relatively even distributions were observed by melanoma stage: I/II (n = 102), III (n = 100), and IV (n = 71). OLS regression resulted in a mapping function of EQ-5D = 0.0037*FACT-M+0.2238 with an R(2) 0.499. CLAD regression resulted in a mapping function of EQ-5D = 0.0042*FACT-M+0.1648 with pseudo R(2) 0.328. When applied to the validation dataset, correlations between observed and predicted values resulted in identical coefficients (r = 0.824, P < 0.001). Though the mapping functions were similar, residuals were smaller at the 20th, 40th, and 60th percentiles using the OLS model. The CLAD derived mapping function resulted in smaller residuals only for patients whose EQ-5D = 1., Conclusions: The OLS mapping function demonstrated better predictive ability and will facilitate the derivation of utilities when direct population preference measures are not available., (Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.)

As interest grows in creating computerized versions of established paper-and-pencil (P&P) questionnaires, it becomes increasingly important to explore whether changing the administration modes of questionnaires affects participants' responses. This study investigated whether mode effects exist when administering the Center for Epidemiologic Studies Depression (CES-D) scale by a personal digital assistant (PDA) versus the classic P&P mode. The Differential Functioning of Items and Tests (DFIT) procedure identified mode effects on the overall test and individual items. A mixed-effects regression model summarized the mode effects in terms of CES-D scores, and identified interactions with covariates. When the P&P questionnaire was administered first, scores were higher on average (2.4-2.8 points) than those of the other administrations (PDA second, PDA first, and P&P second), and all 20 questionnaire items exhibited a statistically significant mode effect. Highly educated people and younger people demonstrated a smaller difference in scores between the two modes. The mode-by-order effect influenced the interpretation of CES-D scores, especially when screening for depression using the established cut-off scores. These results underscore the importance of evaluating the cross-mode equivalence of psychosocial instruments before administering them in non-established modes.